Hostname: page-component-78c5997874-ndw9j Total loading time: 0 Render date: 2024-11-17T09:19:04.673Z Has data issue: false hasContentIssue false
  • English
  • Français

The Bangor Gambling Task: Characterising the Performance of Survivors of Traumatic Brain Injury

Published online by Cambridge University Press:  06 February 2017

Anna-Lynne Ruth Adlam ,
Malcolm Adams ,
Oliver Turnbull ,
Giles Yeates  and
Fergus Gracey
Anna-Lynne Ruth Adlam*
Affiliation:
Child and Adolescent Neuropsychology, School of Psychology, University of Exeter, Exeter, UK
Malcolm Adams
Affiliation:
Department of Psychological Sciences, Norwich Medical School, University of East Anglia, Norwich, UK
Oliver Turnbull
Affiliation:
School of Psychology, University of Bangor, Gwynedd, UK
Giles Yeates
Affiliation:
Oliver Zangwill Centre, The Princess of Wales Hospital, Ely, UK Community Head Injury Service, Aylesbury, UK
Fergus Gracey
Affiliation:
Department of Psychological Sciences, Norwich Medical School, University of East Anglia, Norwich, UK Oliver Zangwill Centre, The Princess of Wales Hospital, Ely, UK
*
Address for correspondence: Dr Anna Adlam, Child and Adolescent Neuropsychology Group, School of Psychology, University of Exeter, Exeter, EX4 4QG, UK. E-mail: [email protected]
Get access

Abstract

The Bangor Gambling Task (BGT, Bowman & Turnbull, 2004) is a simple test of emotion-based decision making, with contingencies varying across five blocks of 20 trials. This is the first study to characterise BGT performance in survivors of traumatic brain injury (TBI) relative to healthy controls. The study also aimed to explore sub-groups (cluster analysis), and identify predictors of task performance (multiple regression). Thirty survivors of TBI and thirty-nine controls completed the BGT and measures of processing speed, pre-morbid IQ, working memory, and executive function. Results showed that survivors of TBI made more gamble choices than controls (total BGT score), although the groups did not significantly differ when using a cut-off score for ‘impaired’ performance. Unexpectedly, the groups did not significantly differ in their performance across the blocks; however, the cluster analysis revealed three subgroups (with survivors of TBI and controls represented in each cluster). Findings also indicated that only age and group were significant predictors of overall BGT performance. In conclusion, the study findings are consistent with an individual difference account of emotion-based decision making, and a number of issues need to be addressed prior to recommending the clinical use of the BGT.

Keywords

Executivesocial cognitionemotion processingmeasurementpsychometrictraumatic brain injury
Type
Articles
Information
Brain Impairment , Volume 18 , Special Issue 1: Disorders of Social Cognition; Advances in Theory, Assessment and Treatment , March 2017 , pp. 62 - 73
Copyright
Copyright © Australasian Society for the Study of Brain Impairment 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

† Author deceased

References

Baddeley, A.D., Emslie, H., & Nimmo-Smith, I. (1992). The speed and capacity of language-processing test (SCOLP). Bury St Edmunds, England: Thames Valley Test Company.Google Scholar
Bechara, A. (2004). The role of emotion in decision-making: evidence from neurological patients with orbitofrontal damage. Brain and Cognition, 55 (1), 30–40.Google Scholar
Bechara, A., Damasio, A.R., Damasio, H., & Anderson, S.W. (1994). Insensitivity to future consequences following damage to human prefrontal cortex. Cognition, 50 (1–3), 7–15.Google Scholar
Bechara, A., Damasio, H., & Damasio, A.R. (2000). Emotion, decision making and the orbitofrontal cortex. Cerebral Cortex, 10 (3), 295–307.CrossRefGoogle ScholarPubMed
Bechara, A., Damasio, H., Tranel, D., & Anderson, S.W. (1998). Dissociation of working memory from decision making within the human prefrontal cortex. Journal of Neuroscience, 18 (1), 428–437.CrossRefGoogle ScholarPubMed
Bechara, A., Dolan, S., Denburg, N., Hindes, A., Anderson, S.W., & Nathan, P.E. (2001). Decision-making deficits, linked to a dysfunctional ventromedial prefrontal cortex, revealed in alcohol and stimulant abusers. Neuropsychologia, 39 (4), 376–389.CrossRefGoogle ScholarPubMed
Bechara, A., Tranel, D., Damasio, H., & Damasio, A.R. (1996). Failure to respond autonomically to anticipated future outcomes following damage to prefrontal cortex. Cerebral Cortex, 6 (2), 215–225.CrossRefGoogle ScholarPubMed
Bowman, C.H., & Turnbull, O.H. (2004). Emotion-based learning on a simplified card game: the Iowa and Bangor gambling tasks. Brain & Cognition, 55 (2), 277–282.Google Scholar
Cauffman, E., Shulman, E.P., Steinberg, L., Claus, E., Banich, M.T., Graham, S., & Woolard, J. (2010). Age differences in affective decision making as indexed by performance on the Iowa gambling task. Developmental Psychology, 46 (1), 193–207 Google Scholar
Cotrena, C., Branco, L.D., Zimmermann, N., Cardoso, C.O., Grassi-Oliveira, R., & Fonseca, R.P. (2014). Impaired decision-making after traumatic brain injury: the Iowa gambling task. Brain Injury, 28 (8), 1070–5.Google Scholar
Damasio, A.R. (1994). Descates error: emotion, reason and the human brain. New York: Avon.Google Scholar
Damasio, A.R. (1996). The somatic marker hypothesis and the possible functions of the prefrontal cortex. Philosophical Transactions of the Royal Society London B Biological Sciences, 351 (1346), 1413–1420.Google Scholar
Damasio, A.R., Adolphs, R., & Damasio, H. (2003). The contributions of the lesion method to the functional neuroanatomy of emotion. In , R.J. Davidson, , , K.R. Scherer, & Goldsmith, H.H. (Eds.), Handbook of affective sciences (pp. 66–92). Oxford: Oxford University Press.Google Scholar
Dunn, B.D., Dalgleish, T., & Lawrence, A.D. (2006). The somatic marker hypothesis: a critical evaluation. Neurosciences & Biobehavioural Reviews, 30 (2), 239–271.Google Scholar
Dunning, D.L., Westgate, B., & Adlam, A.-L. R. (2016). A meta-analysis of working memory impairments in survivors of moderate-to-severe traumatic brain injury. Neuropsychology, 30 (7), 811–9.Google Scholar
Eslinger, P.J., & Damasio, A.R. (1985). Severe disturbance of higher cognition after bilateral frontal lobe ablation: patient EVR. Neurology, 35 (12), 1731–1741.Google Scholar
Franken, I.H.A., & Muris, P. (2005). Individual differences in decision-making. Personality and Individual Differences, 39 (5), 991–998.Google Scholar
Fujiwara, E., Schwartz, M.L., Gao, F., Black, S.E., & Levine, B. (2008). Ventral frontal cortex functions and quantified MRI in traumatic brain injury. Neuropsychologia, 46 (2), 461–474.CrossRefGoogle ScholarPubMed
Gansler, D.A., Jerram, M.W., Vannorsdall, T.D., & Schretlen, D.J. (2011). Does the Iowa gambling task measure executive function?. Archives of Clinical Neuropsychology, 26 (8), 706–17.Google Scholar
Hellawell, D.J., Taylor, R.T., & Pentland, B. (1999). Cognitive and psychosocial outcome following moderate or severe traumatic brain injury. Brain Injury, 13 (7), 489–504.Google Scholar
Hinson, J.M., Jameson, T.L., & Whitney, P. (2002). Somatic markers, working memory, and decision making. Cognitive, Affective & Behavioral Neuroscience, 2 (4), 341–53.CrossRefGoogle ScholarPubMed
Horstmann, A., Villringer, A., & Neumann, J. (2012). Iowa gambling task: there is more to consider than long-term outcome. Using a linear equation model to disentangle the impact of outcome and frequency of gains and losses. Frontiers in Neuroscience, 6, 61.Google Scholar
Jameson, T.L., Hinson, J.M., & Whitney, P. (2004). Components of working memory and somatic markers in decision making. Psychonomic Bulletin & Review, 11 (3), 515–20.Google Scholar
Levine, B., Black, S.E., Cheung, G., Campbell, A., O'Toole, C., & Schwartz, M.L. (2005). Gambling task performance in traumatic brain injury: relationships to injury severity, atrophy, lesion location, and cognitive and psychosocial outcome. Cognitive Behavioural Neurology, 18 (1), 45–54.Google Scholar
Ownsworth, T., & McKenna, K. (2004). Investigation of factors related to employment outcome following traumatic brain injury: a critical review and conceptual model. Disability Rehabilitation, 26 (13), 765–783.Google Scholar
Rimel, R.W., Giordani, B., Barth, J.T., & Jane, J.A. (1982). Moderate head injury: completing the clinical spectrum of brain trauma. Neurosurgery, 11 (3), 344–51.CrossRefGoogle ScholarPubMed
Robertson, I.H., Manly, T., Andrade, J., Baddeley, B.T., & Yiend, J. (1997). 'Oops!': performance correlates of everyday attentional failures in traumatic brain injured and normal subjects. Neuropsychologia, 35 (6), 747–758.CrossRefGoogle ScholarPubMed
Ryterska, A., Jahanshahi, M., & Osman, M. (2013). What are people with Parkinson's disease really impaired on when it comes to making decisions? A meta-analysis of the evidence. Neuroscience and Biobehavioral Reviews, 37 (10 Pt 2), 2836–46.Google Scholar
Salmond, C.H., Menon, D.K., Chatfield, D.A., Pickard, J.D., & Sahakian, B.J. (2005). Deficits in decision-making in head injury survivors. Journal of Neurotrauma, 22 (6), 613–622.Google Scholar
Steingroever, H., Wetzels, R., Horstmann, A., Neumann, J., & Wagenmakers, E.-J. (2013). Performance of healthy participants on the Iowa gambling task. Psychological Assessment, 25 (1), 180–93.Google Scholar
Teasdale, G., & Jennett, B. (1974). Assessment of coma and impaired consciousness. A practical scale. Lancet, 2 (7872), 81–84.Google Scholar
Toplak, M.E., Sorge, G.B., Benoit, A., West, R.F., & Stanovich, K.E. (2010). Decision-making and cognitive abilities: a review of associations between Iowa gambling task performance, executive functions, and intelligence. Clinical Psychology Review, 30 (5), 562–81.Google Scholar
Tranel, D., Bechara, A., & Denburg, N.L. (2002). Asymmetric functional roles of right and left ventromedial prefrontal cortices in social conduct, decision-making, and emotional processing. Cortex; a Journal Devoted to the Study of the Nervous System and Behavior, 38 (4), 589–612.Google Scholar
Turnbull, O.H., Evans, C.E.Y., Bunce, A., Carzolio, B., & O'connor, J. (2005). Emotion-based learning and central executive resources: an investigation of intuition and the Iowa gambling task. Brain and Cognition, 57 (3), 244–7.Google Scholar
van den Bos, R., Homberg, J., & de Visser, L. (2013). A critical review of sex differences in decision-making tasks: focus on the Iowa gambling task. Behavioural Brain Research, 238 (1), 95–108.Google Scholar
Wechsler, D. (1997). Manual for the Wechsler Adult Intelligence Scale – III. London, UK: The Psychological Corporation.Google Scholar
Wilson, B.A., Alderman, N., Burgess, P.W., Emslie, H., & Evans, J.J. (1996). Behavioural assessment of the dysexecutive syndrome (BADS). Bury St Edmunds, UK: Thames Valley Test Company.Google Scholar
Wood, S., Busemeyer, J., Koling, A., Cox, C.R., & Davis, H. (2005). Older adults as adaptive decision makers: evidence from the Iowa gambling task. Psychology and Aging, 20 (2), 220–225.Google Scholar
Zimmermann, N., Pereira, N., Hermes-Pereira, A., Holz, M., Joanette, Y., & Fonseca, R.P. (2015). Executive functions profiles in traumatic brain injury adults: implications for rehabilitation studies. Brain Injury, 29 (9), 1071–1081.Google Scholar